Computational studies of electrocatalytic reactions of interest in the C, N and O cycles
[eng] The global challenge of climate change has underscored the urgent need for sustainable energy solutions that reduce dependence on fossil fuels and mitigate harmful emissions. Electrocatalysis, which enables key reactions for energy conversion, storage, and emissions reduction, plays a critical...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad de Barcelona |
| Repositorio: | Dipòsit Digital de la UB |
| OAI Identifier: | oai:diposit.ub.edu:2445/223693 |
| Acceso en línea: | https://hdl.handle.net/2445/223693 http://hdl.handle.net/10803/695507 |
| Access Level: | acceso abierto |
| Palabra clave: | Electroquímica Catàlisi Electrocatàlisi Catàlisi heterogènia Teoria del funcional de densitat Electrochemistry Catalysis Electrocatalysis Heterogeneus catalysis Density functionals |
| Sumario: | [eng] The global challenge of climate change has underscored the urgent need for sustainable energy solutions that reduce dependence on fossil fuels and mitigate harmful emissions. Electrocatalysis, which enables key reactions for energy conversion, storage, and emissions reduction, plays a critical role in this transition. From the electrochemical reduction of CO2 to the generation of clean hydrogen and the mitigation of nitrogen oxide emissions, electrocatalytic processes are at the forefront of efforts to combat climate change. However, the efficiency and scalability of these processes depend heavily on the design of effective electrocatalysts. This thesis investigates key electrocatalytic reactions within the carbon, nitrogen, and oxygen cycles using density functional theory (DFT). In fact, DFT modeling is a useful approach for uncovering reaction mechanisms, material properties, and solvent interactions, enabling the rational design and optimization of electrocatalytic materials. The study introduces correction methods to refine the activity description of electrocatalysts, emphasizing the importance of solvent–adsorbate interactions and adsorbate- phase error corrections for more accurate simulations. These advancements enable better alignment between computational predictions and experimental results. The thesis also inspects specific catalytic reactions, including the oxygen evolution reaction (OER), acetylene reduction to 1,3-butadiene, and NO hydrogenation. A statistical criterion based on electrochemical symmetry is presented to identify effective OER catalysts. The beneficial influence of catalyst morphology, surface composition, and co-adsorbed anions on acetylene reduction is explored. In the case of NO hydrogenation, the use of catalytic matrices allowed for a deeper understanding of structural sensitivity and selectivity trends across various transition metal electrodes. The comparison of the computational hydrogen electrode (CHE) and the Grand Canonical DFT (GC-DFT) models demonstrates the advantages of GC-DFT in providing a more detailed and accurate description of catalytic behavior under applied potentials. |
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